This project Angel is a high-performance distributed machine learning platform based on the philosophy of Parameter Server. It is tuned for performance with big data from Tencent and has a wide range of applicability and stability, demonstrating increasing advantage in handling higher dimension model. Angel is jointly developed by Tencent and Peking University, taking account of both high availability in industry and innovation in academia. Angel is developed with Java and Scala. It supports running on Yarn and Kubernetes. With the PS Service abstraction, it provides two modules, namely Spark on Angel and Pytorch on Angel separately, which enable integrate the power of Spark/PyTorch and Parameter Server for distributed training. Graph Computing and deep learning frameworks support is under development and will be released in the future.
We welcome everyone interested in machine learning to contribute code, create issues or pull requests. Please refer to Angel Contribution Guide for more detail.
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